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RESEARCH ARTICLE
Climate and community-level determinants of respiratory syncytial virus notifications among Queensland infants, prior to the introduction of the RSV Mother and Infant Protection Program (RSV-MIPP) immunisation initiative
SarahGraham1,10✉Email
BennSartorius2
TomSnelling3
NusratHomaira4,5
AnthonyT.Newall6
MichaelBinks7,8
ColleenLau2
CatherineHughes9
Dr
LisaMcHugh1,10✉
Email
1School of Public Health, Faculty of MedicineUniversity of QueenslandBrisbaneAustralia
2Centre for Clinical Research, Faculty of MedicineUniversity of QueenslandBrisbaneAustralia
3Sydney School of Public Health, Faculty of Medicine and HealthUniversity of SydneySydneyAustralia
4Discipline of Paediatrics and Child Health, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
5Respiratory DepartmentSydney Children’s HospitalSydneyAustralia
6School of Population Health, Faculty of Medicine and HealthUniversity of New South WalesSydneyAustralia
7Maternal and Child Health Division, Menzies School of Health ResearchCharles Darwin UniversityDarwinAustralia
8Women and Kids ThemeSouth Australian Health and Medical Research InstituteAdelaideAustralia
9Consumer/Community RepresentativeImmunisation Foundation of AustraliaSydneyAustralia
10School of Public HealthUniversity of QueenslandLevel 0, Room 011, Bldg 887, 288 Herston Road4006BrisbaneQueenslandAustralia
Sarah Graham1, Benn Sartorius2, Tom Snelling3, Nusrat Homaira4,5, Anthony T. Newall6, Michael Binks7,8, Colleen Lau2, Catherine Hughes9, Lisa McHugh1
1School of Public Health, Faculty of Medicine, University of Queensland, Brisbane, Australia
2Centre for Clinical Research, Faculty of Medicine, University of Queensland, Brisbane, Australia
3Sydney School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
4Discipline of Paediatrics and Child Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
5Respiratory Department, Sydney Children’s Hospital, Sydney, Australia
6School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
7Maternal and Child Health Division, Menzies School of Health Research, Charles Darwin University, Darwin, Australia
8Women and Kids Theme, South Australian Health and Medical Research Institute, Adelaide, Australia
9Consumer/Community Representative, Immunisation Foundation of Australia, Sydney, Australia
Correspondence:
Sarah Graham (s.graham1@uq.edu.au)
School of Public Health, University of Queensland
Level 0, Room 011, Bldg 887, 288 Herston Road, Brisbane, Queensland 4006, Australia
Alternative correspondence:
Dr Lisa McHugh (l.mchugh@uq.edu.au)
School of Public Health, University of Queensland
Level 0, Room 011, Bldg 887, 288 Herston Road, Brisbane, Queensland 4006, Australia
Abstract
Background
Respiratory syncytial virus (RSV) is a highly infectious seasonal respiratory pathogen and a major cause of morbidity in young children. In Australia, RSV is the leading cause of hospitalisation for bronchiolitis and pneumonia among infants aged < 2 years, with the highest severity observed in early infancy. RSV became a nationally notifiable condition in July 2021, and the national RSV Mother and Infant Protection Program (RSV-MIPP) commenced in February 2024. Baseline data on RSV incidence and its determinants are needed to evaluate the effectiveness of the program and identify populations at greatest risk.
Methods
Retrospective cohort study with spatial analysis of all RSV notifications among infants aged < 2 years residing in Queensland between 1 January 2022 and 31 December 2023. Data were obtained from the Queensland Notifiable Conditions System. Incidence rates were calculated by age in months, year, epidemiological week, and climate zone. Spatial analysis methods identified postcode areas with high incidence, and associations in climate zones, and community-level characteristics (remoteness, socioeconomic status, average number of children per family household).
Results
18,683 notifications were recorded among infants aged < 2 years between 2022−2023 (79.73 per 1,000 in 2022; 84.80 per 1,000 in 2023). Incidence was consistently higher among 1-month-olds (187.0 per 1,000) and 12-month-olds (186.3 per 1,000). Compared to tropical climates, incidence was higher in temperate (aRR 1.26, 95% CI 1.13−1.41) and arid/semi-arid zones (aRR 1.18, 95% CI 1.00−1.38), with differences in timing and magnitude of epidemics between climate zones. Higher incidence was observed in areas with larger family sizes (aRR 1.39, 95% CI 1.13−1.72). Remoteness was associated with lower incidence (aRR 0.89, 95% CI 0.87−0.92).
Conclusions
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In Queensland, infants living in areas with larger family sizes and temperate or arid/semi-arid climates experienced higher incidence of RSV infections. Lower recorded incidence in remote areas may be due to undertesting, lower population density, or lower utilisation of centre-based childcare services. Future RSV-MIPP strategies should prioritise climatic and community-level determinants to facilitate equitable access. There is an urgent need for new strategies to protect infants aged > 6 months as the protection from maternal vaccination and birth dose therapeutics wear off.
Key words:
immunisation
vaccination
maternal
child
infant
RSV
Queensland
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Background
Respiratory syncytial virus (RSV) is a highly infectious seasonal respiratory disease and is a significant cause of morbidity among young children[1]. It is the leading cause of hospitalisations for bronchiolitis and pneumonia among Australian infants aged < 2 years, with greatest severity observed in early infancy[1, 2]. Approximately half of all paediatric RSV-related hospital and ICU admissions in Australia are among infants < 6 months of age[2]. Birth shortly before or during RSV season, household crowding, living with siblings, daycare attendance and socioeconomic disadvantage are frequently cited as factors associated with higher risk of RSV infections[35].
Timing of seasonal RSV epidemics varies between Australia’s climate zones[6, 7]. RSV primarily circulates during winter months in temperate regions[7, 8], while tropical areas may experience year-round circulation or monsoonal outbreaks[6, 7]. In contrast, epidemic dynamics in arid zones are poorly understood. Climate change is expected to alter regional epidemic dynamics over time[9].
In 2023−2024, the Therapeutic Goods Administration (TGA) approved two novel preventative agents to reduce RSV incidence and severity in young infants[10, 11]. These include a maternal RSV vaccine offered during the third trimester of pregnancy (Abrysvo), and long-acting RSV-specific monoclonal antibodies for infants (nirsevimab)[12]. Since 01 February 2024, Queensland Health has provided year-round access to a free birth-dose of nirsevimab for all infants. This is available up until 8 months of age, or < 2 years in infants with additional risk factors for severe RSV disease[13]. All states and territories now provide similar programs with varying eligibility requirements, and year-round or seasonal availability (April−September)[12, 14]. Jurisdictional nirsevimab programs form part of the national RSV Mother and Infant Protection Program (RSV-MIPP), which since February 2025 has additionally provided free access to RSV vaccination for all pregnant women under the National Immunisation Program (NIP)[12, 14].
RSV was designated a nationally notifiable condition in July 2021[15]. With nirsevimab introduced in Queensland in February 2024, the years 2022−2023 represent the only complete calendar years of RSV notification data available prior to the introduction of RSV immunisations. Understanding the epidemiology, community-level determinants, and spatiotemporal dynamics of RSV incidence among Queensland infants prior to the introduction of the RSV-MIPP is critical for evaluation of these funded programs, and for achieving optimal and equitable state-wide coverage.
The objectives of this study were to quantify pre-program incidence of RSV notifications among Queensland’s infants aged < 2 years, describe spatiotemporal differences in this incidence between Queensland’s diverse climate zones, and to identify high-incidence spatial clusters and community-level determinants of incidence.
Methods
Setting
Queensland is geographically vast, with an area of approximately 1.73 million km2. The state features significant climate zone diversity, including coastal areas of consistently high humidity and rainfall, a southern inland temperate region, and semi-arid and arid regions toward the state’s interior[16]. Queensland’s population of 5.6 million is concentrated in cities and towns located along the Eastern coastline, with regional and remote populations scattered throughout the northern tropical coast and the expansive dry interior[16, 17]. Queensland’s annual population growth rate of 2.0% is slightly above Australia’s national average 1.8%, with 58,827 births recorded in the year between 30 September 2023−2024[17].
Study design and inclusion criteria
For this retrospective observational study with spatial analysis, we included all infants aged < 2yrs residing in Queensland between 01 January 2022 and 31 December 2023 inclusive (n = 113,555). RSV became a nationally notifiable condition in Australia in July 2021, which falls during the annual RSV season for most of the southern hemisphere[8, 15]. This study period was chosen to capture two complete RSV seasons. Aligned with Queensland Health RSV notification data practices, consecutive RSV notifications for the same infant were counted as discrete infections if they occurred more than180 days apart.
Variables and data sources
RSV case ascertainment
RSV cases were identified from the Queensland Notifiable Conditions System (NOCS). Health service providers are legally required to notify all laboratory-confirmed cases of RSV to NOCS via their local public health unit under the Public Health Act 2005[18]. As such, NOCS captures all laboratory-confirmed cases of RSV in the state based on the Australian national case definition (Supporting Information, box 1)[15].
Population estimates
Population estimates for incidence calculations were obtained from 2021 Australian Bureau of Statistics (ABS) census data[19]. For spatial analysis, census population estimates were obtained by single year of age (0 and 1 year) and postcode area.
Community characteristics
Characteristics for each notification were obtained from the NOCS register, including age and residential postcode. Quintiles of socioeconomic disadvantage for each postcode area were assigned based on the Index of Relative Socioeconomic Disadvantage (IRSAD) within the ABS’s Socioeconomic Index for Areas (SEIFA)[20]. Average number of children per family household by postcode area was derived from ABS 2021 census data[19]. Remoteness of residential postcode area was ascertained from the Accessibility/Remoteness Index of Australia (ARIA+)[21]. This index is assigned based on the distance from usual place of residence to health and other services. Categories include major cities, inner regional, outer regional, remote, and very remote.
Climate zone
Climate zones were determined using the Australian Building Code Board (ABCB) climate zone designation by postcode area[22]. ABCB climate zones are derived from Australian Bureau of Meteorology climate zones, which describe both temperature and humidity[22, 23]. Four out of the total eight Australian climate zones are present in Queensland. Zone 1: high humidity summer, warm winter (tropical); Zone 2: warm humid summer, mild winter (subtropical); Zone 3: hot dry summer, warm winter (arid/semi-arid); and Zone 5: warm temperate[22].
Data analyses
Incidence of RSV notifications were calculated per 1,000 total Queensland population, by 5-year age group and year of notification, then by each completed month of age for infants aged < 2 years. Epidemic curves were constructed to demonstrate weekly incidence among infants, by climate zone of residential postcode and notification year. Poisson regression (generalized linear model) was used to calculate the relative risk (RR) of RSV notifications among infants by postcode and climate zone (index: zone 1, high humidity summer, warm winter), IRSAD quintile (for each one-quintile reduction in advantage) and ARIA designation (for each one-quintile increase in remoteness). Adjusted RRs (aRRs) were subsequently calculated including all covariates. Results are presented as RRs/aRRs with corresponding 95% confidence intervals (95% CI).
We applied Kulldorff’s spatial scan statistic (Poisson model) to detect high-incidence spatial clusters of observed vs expected RSV notifications by year. P-values were obtained through Monte Carlo hypothesis testing (99,999 iterations), and clusters deemed as significant where p < 0.05.
Data were cleaned and analysed using the statistical software package StataSE v.18, and graphs and figures were constructed using StataSE v.18 and Microsoft Excel. Spatial clustering analysis was conducted using SaTScan v10.2.1 and maps developed using ArcGIS v10.8.2. SaTScan outputs do not provide 95% CIs.
Ethics approval
Unconditional ethics approval was attained for this project by the Human Research Ethics Committees (HREC) from The University of Queensland and Queensland Health, approval number HREC/2023/MNHA/96960.
Results
Incidence of RSV notifications
Total Queensland population by 5-year age group
Between 2022−2023 there were 58,019 RSV notifications in Queensland, representing incidence of 5.7 cases per 1,000 total population in 2022, and 5.6 notifications per 1,000 in 2023. By age group, incidence was highest among young children aged < 5 years, with 49.2 notifications per 1,000 children (Supporting Information, Fig. 1). First Nations status was missing for 25% of all notifications (n = 14,647/58,019), with very high missingness in many postcode areas (50–100%). Due to the high overall proportion of missing data and considerable spatial variability in missingness, no further analyses were conducted by First Nations status.
Infants aged < 2 years
Of the 58,019 total Queensland notifications, 18,683 were among infants aged < 2 years (32.2% of all notifications). Overall incidence among infants was 82.26 cases per 1,000 (79.73 cases per 1,000 in 2022; 84.80 cases per 1,000 in 2023) (Table 1). Incidence was higher in 2023 compared to 2022 (RR 1.06, 95% CI 1.03−10.9).
Table 1
Incidence of Queensland RSV notifications per 1000 infants aged < 2 years in 2022–2023, by year and climate zone
Climate zone
Population
aged < 2yrs
2022 incidence, (count)
2023 incidence, (count)
Total 2-year incidence, (count)
Zone 1: High humidity summer, warm winter (tropical)
11,769
68.83 (810)
79.70 (938)
74.26 (1,748)
Zone 2: Warm humid summer, mild winter (subtropical)
91,734
79.85 (7,325)
85.94 (7,884)
82.90 (15,209)
Zone 3: Hot dry summer, warm winter (arid/semi-arid)
4,638
82.15 (381)
54.12 (251)
68.13 (632)
Zone 5: Warm temperate
5,414
99.37 (538)
102.70 (556)
101.03 (1,094)
Totals
113,555
79.73 (9,054)
84.80 (9,629)
82.26 (18,683)
By 1-month age group, incidence of RSV notifications was consistently high from 1–15 months of age (range 155.9−187.0 per 1,000) (Fig. 1; Supporting Information, Table 1). Highest incidence occurred among 1-month-olds (187.0 per 1,000) and 12-month-olds (186.3 per 1,000), with a downward trend after 15 months of age (Fig. 1).
Spatial clustering of notifications by postcode and year
Incidence of RSV notifications differed between residential postcode areas and years (Supporting Information, Fig. 2). Compared to the rest of Queensland, high-incidence clusters occurred in both years within the major population centres of Greater Brisbane (multiple clusters: localities and RRs in Supporting information, Table 2), Townsville and surrounds (2022: RR 1.26, p < 0.01; 2023: RR 1.16, p < 0.01), Darling Downs (2022: RR 1.39, p < 0.01; 2023: RR 1.48, p < 0.01), and the Gold Coast in 2022 (RR 1.20, p < 0.01) (Fig. 2; Supporting Information, Table 2). In 2022, regional clusters were identified in the Aboriginal Shire of Woorabinda (RR 5.20, p < 0.01) and the Longreach area (RR 3.22, p = 0.04) (Fig. 2a, Supporting Information, Table 2). In 2023, regional clusters were identified in the Maryborough-Hervey Bay (RR 1.28, p = 0.01) and Roma areas (RR 2.36, p < 0.01) (Fig. 2b, Supporting Information, Table 2).
Table 2
Poisson regression models investigating community-level determinants of RSV incidence by Australian postcode area in 2022–2023
 
RR1 (95% CI)
Adjusted RRa,b (95% CI)
Climate zone
  
Zone 1: High humidity summer, warm winter (tropical)
Reference category
Reference category
Zone 2: Warm humid summer, mild winter (subtropical)
1.25 (1.15–1.36)*
1.02 (0.90–1.15)
Zone 3: Hot dry summer, warm winter (arid/semi-arid)
1.23 (1.04–1.47)*
1.18 (1.00–1.38)*
Zone 5: Warm temperate
1.46 (1.32–1.61)*
1.26 (1.13–1.41)*
Average number of children per family household
1.24 (0.99–1.56)
1.39 (1.13–1.72)*
Socioeconomic disadvantage
(IRSAD quintile)c
1.02 (1.00–1.04)*
1.00 (0.98–1.01)
Remoteness
(ARIA quintile)d
0.91 (0.88–0.94)*
0.89 (0.87–0.92)*
*Statistically significant results (p < 0.05 level).
aRisk Ratio; obtained using Poisson regression.
bAdjusted models include climate zone, average number of children per family household, socioeconomic disadvantage (IRSAD quintile) and remoteness (ARIA quintile), by Australian postcode area
cRR for each 1-unit increase in socioeconomic disadvantage of postcode area
dRR for each 1-unit increase in remoteness of postcode area
Community characteristics and RSV incidence
In the unadjusted model, there was weak evidence of increased incidence for each one-quintile increase in socioeconomic disadvantage (RR 1.02, 95% CI 1.00−1.04). This association was no longer statistically significant following adjustment (aRR 1.00, 95% CI 0.98−1.01) (Table 2). In contrast, the incidence of RSV notifications decreased significantly with each one-quintile increase in remoteness of postcode area(RR 0.91, 95% CI 0.88−0.94; aRR 0.89, 95% CI 0.84−0.94). In addition, there was a 39% increase in RSV incidence observed for each additional child in the mean number of children per family household by postcode (aRR 1.39, 95% CI 1.13−1.72) (Table 2).
RSV incidence by climate zone
The highest crude incidence among infants aged < 2 years occurred in warm temperate areas (zone 5, 101.0 per 1 000 infants), and this was consistently observed across 2022 and 2023 (Table 1). In the adjusted model (Table 2), arid/semi-arid (zone 3, aRR 1.18, 95% CI 1.00−1.38) and warm temperate areas (zone 5, aRR 1.26, 95% CI 1.13−1.41) had higher overall incidence compared to tropical areas (zone 1). There was no difference in incidence detected between tropical and subtropical areas (zone 2, aRR 1.02, 95% CI 0.90−1.15) (Table 2). Climate zone 4 is not present in Queensland.
Variation in timing of RSV season by climate zone
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In 2022, incidence of RSV notifications by epidemiological week showed a monophasic pattern typical of a southern hemisphere annual late-autumn to mid-winter peak (May − July). In 2023, most notifications occurred during autumn (March − May). Weekly RSV notifications for both years showed distinct differences in their distribution between climate zones. In 2022, there was a one-month difference between the peak of RSV notifications for climate zones 1 and 2 and 2 and 3, and multiple peaks throughout the year for zone 3 (Fig. 3a;
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Supporting Information, table 3
). In 2023, there was year-round elevated baseline RSV notifications for climate zones 1 and 2 with peaks occurring between March − May. Multiple peaks of notifications occurred in climate zones 3 and 5, with bimodal peaks in zone 5 during the winter months. There was a difference of approximately two months between peaks for climate zones 1, 3 and 5 (Fig. 3b; Supporting Information, table 3).
Discussion
Among infants aged < 2 years, incidence of RSV was persistently high from 1–15 months of age. Highest incidence was recorded among 1-month-olds and 12-month-olds, the latter of whom are currently ineligible for protection with nirsevimab under the RSV-MIPP unless they have additional risk factors for severe disease. We identified high-incidence spatial clusters of RSV notifications in both major population centres and regional areas and found that remoteness of residence and number of children per family household may be important community-level determinants of RSV incidence. The role of community-level socioeconomic disadvantage in determining incidence was less clear, possibly due to unmeasured confounding from socioeconomic differences in utilisation of healthcare, childcare, and other services. RSV incidence varied between Queensland’s climate zones, with greater incidence recorded in lower humidity areas with a more distinct winter season. Timing and magnitude of RSV epidemics among infants also differed between Queensland’s climate zones, highlighting differences in key risk periods for RSV transmission across the state.
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Given the frequency of severe outcomes among infants[1, 2] and compelling evidence of a casual association with the onset of childhood asthma following RSV infections in the first year of life[2, 24], high incidence of RSV among infants represents a major public health issue. The RSV-MIPP is likely to reduce incidence and severity among Australia’s youngest infants, however we observed persistently high RSV incidence from birth until 15 months of age. Maternal RSV vaccination and nirsevimab administered at birth have each been demonstrated to protect infants until approximately 6 months of age[25, 26]. Older infants > 6 months of age are unlikely to be adequately protected by current interventions. Options to extend the duration of protection against RSV into later infancy should be explored.
Family size, household crowding, and RSV transmission dynamics are important considerations in future program planning. Household transmission between siblings is a major driver of RSV incidence, with children who are exposed to RSV at school or daycare subsequently spreading infections to other children in their home[4, 27]. In light of this, nirsevimab and maternal RSV vaccination may be particularly cost-effective when used to protect infants who live with older preschool or school-aged siblings for whom RSV immunisation is not yet available[12]. Childcare centres may represent an effective setting to raise awareness of RSV and its prevention among parents.
The effect of community-level socioeconomic disadvantage on RSV incidence among infants was not statistically significant in the adjusted model, and increasing remoteness appeared to be associated with lower RSV incidence. Considering that remote and disadvantaged communities in Australia are often burdened by established risk factors for RSV transmission such as household crowding[28], these results should be interpreted cautiously. Our findings may be explained by lower rates of RSV testing in more socially disadvantaged or remote regions, smaller populations in remote areas, or residual effects of the COVID-19 pandemic. It is also plausible that remoteness may be associated with decreased incidence of RSV among infants due to lower and/or later initiation of attendance at formal childcare services in rural and remote areas of Queensland, where service availability is often limited[29]. Similarly, the high cost of centre-based childcare in Australia is associated with reduced attendance among children from socioeconomically disadvantaged households[29]. Future studies may elucidate whether access to local childcare services is an independent spatial determinant of RSV notifications. Despite our observations, it is well established that socioeconomically disadvantaged and remote residents experience significant cost, availability, distance, and cultural barriers to accessing health care services in Australia[30]. Prioritising equity in new RSV prevention programs is critical to ensure optimal coverage among all eligible infants.
Queensland’s tropical and subtropical zones demonstrated year-round circulation of RSV with lower-incidence peaks, which occurred earlier in 2023 compared to other zones. Previous studies have found peaks occurring during periods of high rainfall in North Queensland and other tropical regions[6, 8]; with lower overall incidence thought to be determined by a combination of consistent high humidity and lack of a distinctly cooler winter season[6]. Findings were similar for subtropical areas, albeit with a more distinct seasonal peak in 2022 than observed in the tropics. Whilst overall incidence was lower in the tropical and subtropical zones compared to other parts of Queensland, significant clusters were still identified in several densely populated areas within these zones.
Epidemics in warm temperate (zone 5) and arid/semi-arid (zone 3) regions with distinct winter seasons were more discrete, with consistent high-incidence seasonal peaks observed in zone 5 across 2022−2023. Incidence in the arid/semi-arid interior regions of Queensland was high in 2022, but this was not repeated in 2023. There is some evidence that RSV outbreaks may occur biennially in some non-tropical regions of Australia[7], and future years of RSV notification data will clarify whether this is true for Queensland’s dry interior. Understanding these patterns will be necessary for targeted vaccination program planning and rollout.
Limitations
Notification data inherently underestimates true RSV incidence, as testing is prerequisite to notification. Evidence from Western Australia suggests that the true incidence of RSV among children aged < 5 years may be 30−57% higher than captured through RSV notifications[31], and this estimate may be conservative. Incidence in our study is therefore likely to be underestimated, particularly among populations with lower rates of testing due to poorer access to health services, milder symptoms, or in lower-risk age groups.
Due to high missingness for First Nations status with considerable spatial variation, we were unable to reliably assess spatial incidence of RSV notifications among First Nations infants. Our study did however identify a major RSV cluster among infants in the Woorabinda Shire, where 91.6% of residents identify as a First Nations person[32]. Data sources with greater completeness for this important variable and improved capture of First Nations status at the time of RSV testing are necessary to understand community-level determinants of RSV incidence among First Nations infants.
It was not possible to identify notifications among siblings from the same household in our unlinked dataset. Mean number of children per family household in each postcode area was examined as a community-level determinant of RSV incidence, however infants with RSV notifications may have lived in households with an above or below average number of children compared to their postcode area. This is also true of IRSAD quintile, as individual infants may have greater or lesser degrees of socioeconomic advantage compared to their area of residence.
Whilst our findings are relevant for Queensland, further research is required to ascertain whether these findings are generalisable to other jurisdictions.
Conclusion
The introduction of the RSV-MIPP is likely to reduce incidence of RSV infections and severe outcomes among younger infants, however older infants are unlikely to be adequately protected. Protective strategies for these infants warrant further attention. We found higher incidence of RSV notifications in 2022−2023 in areas with larger family sizes, and in areas with distinctly cooler and lower humidity winters. Lower RSV incidence observed in remote areas may be attributable to lower rates of testing, or limited access to childcare services. Community-level determinants of RSV incidence should be considered in RSV-MIPP evaluation and planning.
List of abbreviations
ABCB
The Australian Building Code Board
ABS
Australian Bureau of Statistics
ARIA+
Accessibility/Remoteness Index of Australia
aRRs
Adjusted relative risks
CI
Confidence interval
EL1
Emerging Leadership
HREC
Human Research Ethics Committees
IRSAD
Index of Relative Socioeconomic Disadvantage
NIP
National Immunisation Program
NOCS
Queensland Notifiable Conditions System
RR
Relative risk
RSV-MIPP
Respiratory Syncytial Virus Mother and Infant Protection Program
RSV
Respiratory Syncytial Virus
SEIFA
Socioeconomic Index for Areas
TGA
Therapeutic Goods Administration
Declarations
Ethics approval and consent to participate
Unconditional ethics approval was attained for this project by the Human Research Ethics Committees (HREC) from The University of Queensland and Queensland Health, approval number HREC/2023/MNHA/96960. A waiver of individual informed consent was requested from and granted by The University of Queensland HREC due to the large size of the study and the use of de-identified data. The study was conducted in accordance with the ethical principles of the Declaration of Helsinki.
Consent for publication
Not applicable
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Data Availability
ABS 2021 census data utilised in this study can be accessed at the following URL: [https://www.abs.gov.au/census/find-census-data/datapacks](https:/www.abs.gov.au/census/find-census-data/datapacks)The Australian Building Codes Board climate zone mapping dataset can be accessed at the following URL: [https://data.gov.au/data/dataset/australian-climate-zone-map](https:/data.gov.au/data/dataset/australian-climate-zone-map)Deidentified individual patient-level RSV notification data utilised in this study cannot be made publicly available for ethical and privacy reasons. Requests to the corresponding author for the data will be considered on a case-by-case basis.
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Competing Interests
N.H. has at times received consultation fees from Sanofi, Pfizer and Merck Sharp & Dohme Australia, and is a chief investigator of an industry-sponsored study on RSV complications. C.H. is employed by the Immunisation Foundation of Australia, which has received unrestricted educational grants from Sanofi, Pfizer, and GSK to support RSV awareness activities. S.G., B.S., T.S., A.N, M.B., C.L., and L.Mc. have no potential conflicts of interest to declare.
C.H. is employed by the Immunisation Foundation of Australia, which has received unrestricted educational grants from Sanofi, Pfizer, and GSK to support RSV awareness activities.
S.G., B.S., T.S., A.N, M.B., C.L., and L.Mc. have no potential conflicts of interest to declare.
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Funding
This work was supported by an Emerging Leadership (EL1) National Health and Medical Research Council Investigator Grant [GNT2016407 to L.Mc.], a National Health and Medical Research Council Investigator Grant [GNT1193826 to C.L.], and a Medical Research Future Fund Investigator Grant [MRF1195153 to T.S.].
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Author Contribution
S.G. and B.S. contributed to the data analysis methodologies, all results and contributed to all edited versions of manuscript drafts. T.S., A.N., M.B., C.L., and L.Mc. contributed to the design of the study, reviewed study results and edited all version of manuscript drafts. L.Mc. developed the study concept, obtained ethics approvals and the ensuing data, oversaw the management of the project, and supervised S.G. All authors read and approved the final manuscript.
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Acknowledgement
The authors would like to acknowledge Dr Bianca Middleton and Alexa Dakiniewich for their input into the study. We would also like to thank the Queensland Department of Health data custodians for the Notifiable Conditions System.
References
1.
Li Y, Wang X, Blau DM, Caballero MT, Feikin DR, Gill CJ, et al. Global, regional, and national disease burden estimates of acute lower respiratory infections due to respiratory syncytial virus in children younger than 5 years in 2019: A systematic analysis. Lancet. 2022;399(10340):2047–64.
2.
Self A, Van Buskirk J, Clark J, Cochrane JE, Knibbs L, Cass-Verco J, et al. Respiratory syncytial virus disease morbidity in Australian infants aged 0 to 6 months: A systematic review with narrative synthesis. BMC Public Health. 2023;23(1):2560.
3.
Cacho F, Gebretsadik T, Anderson LJ, Chappell JD, Rosas-Salazar C, Ortiz JR, et al. Respiratory syncytial virus prevalence and risk factors among healthy term infants, United States. Emerg Infect Dis. 2024;30(10):2199–202.
4.
Colosia AD, Masaquel A, Hall CB, Barrett AM, Mahadevia PJ, Yogev R. Residential crowding and severe respiratory syncytial virus disease among infants and young children: A systematic literature review. BMC Infect Dis. 2012;12:95.
5.
Gantenberg JR, van Aalst R, Bhuma MR, Limone B, Diakun D, Smith DM, et al. Risk analysis of respiratory syncytial virus among infants in the United States by birth month. J Pediatr Infect Dis Soc. 2024;13(6):317–27.
6.
Paynter S, Ware RS, Sly PD, Weinstein P, Williams G. Respiratory syncytial virus seasonality in tropical Australia. Aust N Z J Public Health. 2015;39(1):8–10.
7.
Hogan AB, Anderssen RS, Davis S, Moore HC, Lim FJ, Fathima P, et al. Time series analysis of RSV and bronchiolitis seasonality in temperate and tropical Western Australia. Epidemics. 2016;16:49–55.
8.
Obando-Pacheco P, Justicia-Grande AJ, Rivero-Calle I, Rodriguez-Tenreiro C, Sly P, Ramilo O, et al. Respiratory syncytial virus seasonality: A global overview. J Infect Dis. 2018;217(9):1356–64.
9.
Baker RE, Mahmud AS, Wagner CE, Yang W, Pitzer VE, Viboud C, et al. Epidemic dynamics of respiratory syncytial virus in current and future climates. Nat Commun. 2019;10(1):5512.
10.
Therapeutic Goods Administration. Beyfortus - Australian prescription medicine decision summary. [https://www.tga.gov.au/resources/auspmd/beyfortus]. Accessed April 2025.
11.
Therapeutic Goods Administration. Abrysvo (RSV vaccine) - Australian prescription medicine decision summary. [https://www.tga.gov.au/resources/auspmd/abrysvo-rsv-vaccine]. Accessed April 2025.
12.
Australian Immunisation Handbook. Respiratory syncytial virus (RSV). [https://immunisationhandbook.health.gov.au/contents/vaccine-preventable-diseases/respiratory-syncytial-virus-rsv]. Accessed April 2025.
13.
Queensland Health. Queensland Paediatric Respiratory Syncytial Virus Prevention Program. [https://www.health.qld.gov.au/clinical-practice/guidelines-procedures/diseases-infection/immunisation/paediatric-rsv-prevention-program]. Accessed April 2025.
14.
National Centre for Immunisation Research and Surveillance. Respiratory syncytial virus (RSV). Frequently asked questions (FAQs). [https://ncirs.org.au/ncirs-fact-sheets-faqs-and-other-resources/respiratory-syncytial-virus-rsv-frequently-asked]. Accessed April 2025.
15.
Australian Government Department of Health and Aged Care. Respiratory syncytial virus – Surveillance case definition. [https://www.health.gov.au/resources/publications/respiratory-syncytial-virus-surveillance-case-definition]. Accessed April 2025.
16.
Neldner VJ, Butler DW, Guymer GP. April. Queensland’s regional ecosystems: Building and maintaining a biodiversity inventory, planning framework and information system for Queensland. [https://www.publications.qld.gov.au/ckan-publications-attachments-prod/resources/42657ca4-848f-4d0e-91ab-1b475faa1e7d/qld-regional-ecosystems.pdf]. Accessed 2025.
17.
Australian Bureau of Statistics. National, state and territory population. [https://www.abs.gov.au/statistics/people/population/national-state-and-territory-population/sep-2024]. Accessed April 2025.
18.
Queensland Health. Notifiable conditions register. [https://www.health.qld.gov.au/clinical-practice/guidelines-procedures/diseases-infection/notifiable-conditions/register]. Accessed April 2025.
19.
Australian Bureau of Statistics. Census DataPacks – 2021. [https://www.abs.gov.au/census/find-census-data/datapacks]. Accessed June 2024.
20.
Australian Bureau of Statistics. Socio-Economic Indexes for Areas (SEIFA): Technical Paper. [https://www.abs.gov.au/statistics/detailed-methodology-information/concepts-sources-methods/socio-economic-indexes-areas-seifa-technical-paper/2021]. Accessed April 2025.
21.
Australian Bureau of Statistics. Remoteness Areas: Australian Statistical Geography Standard (ASGS) Edition 3. [https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/remoteness-structure/remoteness-areas]. Accessed October 2024.
22.
Australian Building Codes Board. Climate zone map. [https://www.abcb.gov.au/resources/climate-zone-map]. Accessed October 2024.
23.
Bureau of Meteorology. Climate classifications. [http://www.bom.gov.au/climate/maps/averages/climate-classification/]. Accessed October 2024.
24.
Homaira N, Briggs N, Oei JL, Hilder L, Bajuk B, Jaffe A, et al. Association of age at first severe respiratory syncytial virus disease with subsequent risk of severe asthma: A population-based cohort study. J Infect Dis. 2019;220(4):550–6.
25.
Hammitt LL, Dagan R, Yuan Y, Baca Cots M, Bosheva M, Madhi SA, et al. Nirsevimab for prevention of RSV in healthy late-preterm and term infants. N Engl J Med. 2022;386(9):837–46.
26.
Kampmann B, Madhi SA, Munjal I, Simoes EAF, Pahud BA, Llapur C, et al. Bivalent prefusion F vaccine in pregnancy to prevent RSV illness in infants. N Engl J Med. 2023;388(16):1451–64.
27.
Jacoby P, Glass K, Moore HC. Characterizing the risk of respiratory syncytial virus in infants with older siblings: A population-based birth cohort study. Epidemiol Infect. 2017;145(2):266–71.
28.
Australian Institute of Health and Welfare. Australia’s children: overcrowding. [https://www.aihw.gov.au/reports/children-youth/australias-children/contents/housing/overcrowding]. Accessed April 2025.
29.
Australian Competition and Consumer Commission. Childcare inquiry final report. [https://www.accc.gov.au/inquiries-and-consultations/childcare-inquiry-2023/december-2023-final-report]. Accessed April 2025.
30.
Shukla N, Pradhan B, Dikshit A, Chakraborty S, Alamri AM. A review of models used for investigating barriers to healthcare access in Australia. Int J Environ Res Public Health. 2020;17(11):4087.
31.
Gebremedhin AT, Hogan AB, Blyth CC, Glass K, Moore HC. Developing a prediction model to estimate the true burden of respiratory syncytial virus (RSV) in hospitalised children in Western Australia. Sci Rep. 2022;12(1):332.
32.
Australian Bureau of Statistics. Woorabinda 2021, census all persons quickstats. [https://www.abs.gov.au/census/find-census-data/quickstats/2021/LGA37550]. Accessed October 2024.
Manuscript. tables and figures.
A
Fig. 1
Number and incidence of RSV infections in Queensland infants aged < 2 years by month of age, 2022–2023 inclusive.
Click here to Correct
Click here to Correct
Cluster key
a.
a) 2022: 1 – Darling Downs region (Toowoomba), 2 – Samford (Greater Brisbane), 3 – Aboriginal Shire of Woorabinda, 4 – Townsville and surrounds, 5 – Redland (Greater Brisbane), 6 – Gold Coast, 7 – Longreach
b.
b) 2023: 8 – Darling Downs (Gatton), 9 – Logan (Greater Brisbane), 10 – Moreton Bay (Greater Brisbane/Sunshine Coast), 11 – Roma, 12 – Townsville and surrounds, 13 – Hervey Bay/Maryborough
A
Fig. 2
Cluster analysis of Queensland RSV notifications per 1,000 infants aged < 2 years by year and residential postcode, with ABCB climate zone boundaries
A
Fig. 3
Incidence of RSV notifications in Queensland per 1,000 infants aged < 2 years, by year, epidemiological week, and climate zone of residence
Supporting Information
Click here to Correct
Confirmed case – Definitive laboratory evidence only
Laboratory definitive evidence:
1. Isolation of respiratory syncytial virus by a cell culture
OR
2. Detection of respiratory syncytial virus by nucleic acid testing
OR
3. Detection of respiratory syncytial virus antigen
OR
4. Seroconversion, or a significant increase in antibody level such as a fourfold or greater rise in titre, to respiratory syncytial virus between paired sera of immunoglobulin G (IgG) or total antibody
Supporting information, box 1: Respiratory syncytial virus Australian national notifiable diseases case definition, from: https://www.health.gov.au/resources/publications/respiratory-syncytial-virus-surveillance-case-definition (viewed April 2025).
Click here to Correct
Supporting information, Fig. 1
. Number and incidence of RSV notifications in Queensland 2022–2023 inclusive.
Supporting information, table 1.
Number and incidence of RSV infections per 1,000 infants aged < 2 years in Queensland by completed month of age, 2022–2023 inclusive.
Infant age (months)
RSV notifications (count)
Incidence per 1,000a
0
550
112.5
1
914
187.0
2
802
164.1
3
779
159.4
4
779
159.4
5
796
162.9
6
813
166.4
7
845
172.9
8
845
172.9
9
870
178.0
10
825
168.8
11
880
180.1
12
915
186.3
13
907
184.7
14
852
173.5
15
904
184.0
16
795
161.9
17
751
152.9
18
704
143.3
19
670
136.4
20
635
129.3
21
640
130.3
22
638
129.9
23
575
117.1
TOTAL
18,684
158.9
aPopulation denominators estimated from ABS 2021 census single year of age estimates for Queensland
Click here to Correct
Supporting information, Fig. 2
. Incidence of RSV notifications by postcode (location based on population weighted centroid) in Queensland per 1,000 infants aged < 2 years
Supporting information, table 2.
Spatial cluster analysis of Queensland RSV infections among infants aged < 2 years, 2022–2023
Location of spatial clusters,
by year
Cases (n)
O/Ea ratio
Relative risk (p-value)
Climate zoneb
2022
    
1: Darling Downs region (Toowoomba)
1189
1.34
1.39 (< 0.001)
2 & 5
2: Samford (Greater Brisbane)
1060
1.25
1.28 (< 0.001)
2
3: Aboriginal Shire of Woorabinda
24
5.19
5.20 (< 0.001)
3
4: Townsville and surrounds
502
1.24
1.26 (< 0.001)
1
5: Redland (Greater Brisbane)
496
1.17
1.18 (< 0.001)
2
6: Gold Coast
410
1.19
1.20 (0.008)
2
7: Longreach
19
3.21
3.22 (0.039)
3
2023
    
8: Darling Downs (Gatton)
1223
1.42
1.48 (< 0.001)
2 & 5
9: Logan (Greater Brisbane)
755
1.33
1.36 (< 0.001)
2
10: Moreton Bay (Greater Brisbane/Sunshine Coast)
1016
1.13
1.14 (< 0.001)
2
11: Roma
56
2.35
2.36 (< 0.001)
3
12: Townsville and surrounds
450
1.15
1.16 (0.003)
1
13: Hervey Bay-Maryborough
357
1.27
1.28 (0.009)
2
aObserved/Expected ratio
bClimate zone key:
1 = High humidity summer, warm winter (tropical)
2 = Warm humid summer, mild winter (subtropical)
3 = Hot dry summer, warm winter (semi-arid/arid)
5 = Warm temperate
Supporting information, table 3.
Incidence of RSV notifications in Queensland per 1,000 infants aged < 2 years, by year, epidemiological week and climate zone of residence
Epidemiological week, by year
Incidencea, zone 1 (tropical)
Incidencea, zone 2 (subtropical)
Incidencea, zone 3 (arid/semi-arid)
Incidencea, zone 5 (warm temperate)
2022
    
1
0.17
0.14
0.22
0.00
2
0.42
0.11
0.00
0.00
3
0.34
0.07
0.00
0.00
4
0.42
0.08
0.00
0.00
5
0.08
0.03
0.00
0.00
6
0.17
0.11
0.00
0.00
7
0.00
0.10
0.00
0.00
8
0.34
0.17
0.00
0.00
9
0.42
0.35
0.00
0.00
10
0.51
0.32
0.00
0.18
11
0.51
0.50
0.00
0.00
12
0.42
0.53
0.00
0.18
13
0.76
0.69
0.00
0.00
14
0.42
1.09
0.00
0.18
15
0.25
1.38
0.00
0.37
16
0.68
1.48
0.00
0.18
17
0.17
1.61
0.00
0.37
18
0.68
2.86
0.43
1.29
19
0.76
3.56
0.22
2.40
20
2.12
6.05
0.65
4.06
21
1.78
7.38
0.86
7.20
22
2.55
8.18
1.51
6.83
23
3.65
6.78
1.51
10.90
24
5.01
6.02
3.45
12.74
25
5.78
5.10
6.47
10.90
26
5.86
4.87
10.78
7.39
27
4.84
3.67
6.04
5.73
28
3.14
3.10
7.33
5.73
29
3.57
2.33
5.61
3.32
30
3.23
1.68
8.84
4.99
31
2.46
1.67
4.74
3.51
32
1.70
1.28
6.04
3.32
33
1.53
0.81
4.53
1.85
34
1.95
0.69
1.72
1.11
35
1.36
0.43
2.37
1.11
36
0.85
0.46
2.37
0.18
37
1.36
0.41
1.08
1.29
38
1.10
0.38
0.65
0.37
39
0.25
0.27
1.51
0.37
40
1.02
0.16
0.43
0.00
41
0.34
0.31
0.86
0.37
42
0.51
0.19
0.00
0.00
43
0.93
0.26
0.43
0.00
44
0.17
0.25
0.22
0.37
45
0.34
0.15
0.43
0.00
46
0.51
0.23
0.00
0.00
47
0.42
0.26
0.65
0.00
48
0.59
0.24
0.22
0.18
49
0.85
0.26
0.00
0.18
50
0.85
0.27
0.00
0.00
51
0.17
0.27
0.00
0.18
52
0.42
0.26
0.00
0.00
2023
    
1
0.51
0.23
0.00
0.18
2
0.42
0.23
0.00
0.00
3
0.42
0.46
0.00
0.18
4
1.02
0.60
0.00
0.18
5
1.44
0.57
0.00
0.18
6
1.19
0.78
0.22
0.18
7
1.19
1.11
0.00
0.18
8
1.27
1.24
0.43
0.18
9
1.87
1.41
0.65
0.00
10
2.46
1.96
0.86
0.37
11
3.48
2.56
0.43
0.18
12
3.31
3.25
0.43
0.37
13
5.44
3.67
0.43
1.48
14
3.48
4.14
1.29
1.11
15
4.76
4.06
0.86
1.48
16
3.57
3.36
0.43
0.92
17
3.91
3.39
0.65
2.03
18
4.25
3.66
1.94
2.22
19
2.72
2.59
1.72
2.22
20
1.78
2.85
2.16
4.62
21
1.78
3.15
2.80
6.28
22
1.61
2.76
4.31
9.42
23
0.93
2.67
2.16
9.24
24
0.76
2.37
1.29
9.24
25
0.51
2.04
2.16
7.02
26
1.02
2.04
1.94
5.54
27
0.93
1.87
3.23
8.31
28
0.76
1.67
1.72
5.73
29
1.19
1.68
3.02
4.06
30
1.10
1.42
1.51
3.69
31
1.44
1.78
1.29
2.59
32
0.93
1.19
1.29
1.85
33
1.02
1.45
2.37
1.66
34
0.59
1.31
1.08
1.11
35
0.68
1.42
2.37
0.18
36
0.85
1.26
1.72
2.59
37
1.53
1.36
1.29
0.92
38
0.76
1.24
0.65
1.29
39
0.68
0.98
1.29
0.55
40
0.51
0.99
0.86
0.92
41
1.10
0.85
0.43
0.37
42
0.93
0.76
0.00
0.18
43
0.93
0.80
0.43
0.18
44
0.51
0.75
0.00
0.55
45
0.68
0.59
0.43
0.00
46
0.51
0.76
0.22
0.18
47
0.51
0.69
0.00
0.18
48
1.19
0.56
0.43
0.00
49
1.19
0.76
0.00
0.00
50
1.27
1.01
0.00
0.00
51
1.87
0.98
0.86
0.37
52
0.85
0.66
0.43
0.18
aIncidence per 1,000 infants
Climate and community-level determinants of respiratory syncytial virus notifications among Queensland infants, prior to the introduction of the RSV Mother and Infant Protection Program (RSV-MIPP) immunisation initiative
Total words in MS: 5079
Total words in Title: 2
Total words in Abstract: 343
Total Keyword count: 7
Total Images in MS: 5
Total Tables in MS: 6
Total Reference count: 33